Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2005: (UTC) administrator
Metadata Last Update2020: (UTC) administrator
Citation KeyBustosKim:2005:ImMaEn
TitleReconstruction-diffusion: An improved maximum entropy reconstruction algorithm based on the robust anisotropic diffusion
Access Date2021, Dec. 07
Number of Files1
Size194 KiB
Context area
Author1 Bustos, Harold Ivan Angulo
2 Kim, Hae Yong
Affiliation1 Universidade Federal do Rio Grande do Norte
2 Universidade de São Paulo
EditorRodrigues, Maria Andréia Formico
Frery, Alejandro César
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
Conference LocationNatal
Date9-12 Oct. 2005
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2005-07-13 18:55:31 :: Harold -> banon ::
2005-07-13 19:31:27 :: banon -> Harold ::
2008-07-17 14:11:00 :: Harold -> banon ::
2008-08-26 15:17:02 :: banon -> administrator ::
2009-08-13 20:37:50 :: administrator -> banon ::
2010-08-28 20:01:18 :: banon -> administrator ::
2020-02-19 03:19:14 :: administrator -> :: 2005
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
KeywordsMaximum Entropy
Robust Anisotropic Diffusion
AbstractMaximum entropy (MENT) is a well-known image reconstruction algorithm. If only a small amount of acquisition data is available, this algorithm converges to a noisy and blurry image. We propose an improvement to this algorithm that consists on applying alternately the MENT reconstruction and the robust anisotropic diffusion (RAD). We have tested this idea for the re-construction from full-angle parallel acquisition data, but the idea can be applied to any data acquisition sce-nario. The new technique has yielded surprisingly clear images with sharp edges even using extremely small amount of projection data.
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Target Filebustosh_entropy.pdf
User GroupHarold
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